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Prediction accuracy of L- and M-cone based human pupil light models

Multi-channel LED luminaires offer a powerful tool to vary retinal receptor signals while keeping visual parameters such as color or brightness perception constant. This technology could provide new fields of application in indoor lighting since the spectrum can be enhanced individually to the users...

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Autores principales: Zandi, Babak, Klabes, Julian, Khanh, Tran Quoc
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7335057/
https://www.ncbi.nlm.nih.gov/pubmed/32620793
http://dx.doi.org/10.1038/s41598-020-67593-3
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author Zandi, Babak
Klabes, Julian
Khanh, Tran Quoc
author_facet Zandi, Babak
Klabes, Julian
Khanh, Tran Quoc
author_sort Zandi, Babak
collection PubMed
description Multi-channel LED luminaires offer a powerful tool to vary retinal receptor signals while keeping visual parameters such as color or brightness perception constant. This technology could provide new fields of application in indoor lighting since the spectrum can be enhanced individually to the users’ favor or task. One possible application would be to optimize a light spectrum by using the pupil diameter as a parameter to increase the visual acuity. A spectral- and time-dependent pupil model is the key requirement for this aim. We benchmarked in our work selected L- and M-cone based pupil models to find the estimation error in predicting the pupil diameter for chromatic and polychromatic spectra at 100 cd/m(2). We report an increased estimation error up to 1.21 mm for 450 nm at 60–300 s exposure time. At short exposure times, the pupil diameter was approximately independent of the used spectrum, allowing to use the luminance for a pupil model. Polychromatic spectra along the Planckian locus showed at 60–300 s exposure time, a prediction error within a tolerance range of ± 0.5 mm. The time dependency seems to be more essential than the spectral dependency when using polychromatic spectra.
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spelling pubmed-73350572020-07-07 Prediction accuracy of L- and M-cone based human pupil light models Zandi, Babak Klabes, Julian Khanh, Tran Quoc Sci Rep Article Multi-channel LED luminaires offer a powerful tool to vary retinal receptor signals while keeping visual parameters such as color or brightness perception constant. This technology could provide new fields of application in indoor lighting since the spectrum can be enhanced individually to the users’ favor or task. One possible application would be to optimize a light spectrum by using the pupil diameter as a parameter to increase the visual acuity. A spectral- and time-dependent pupil model is the key requirement for this aim. We benchmarked in our work selected L- and M-cone based pupil models to find the estimation error in predicting the pupil diameter for chromatic and polychromatic spectra at 100 cd/m(2). We report an increased estimation error up to 1.21 mm for 450 nm at 60–300 s exposure time. At short exposure times, the pupil diameter was approximately independent of the used spectrum, allowing to use the luminance for a pupil model. Polychromatic spectra along the Planckian locus showed at 60–300 s exposure time, a prediction error within a tolerance range of ± 0.5 mm. The time dependency seems to be more essential than the spectral dependency when using polychromatic spectra. Nature Publishing Group UK 2020-07-03 /pmc/articles/PMC7335057/ /pubmed/32620793 http://dx.doi.org/10.1038/s41598-020-67593-3 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Zandi, Babak
Klabes, Julian
Khanh, Tran Quoc
Prediction accuracy of L- and M-cone based human pupil light models
title Prediction accuracy of L- and M-cone based human pupil light models
title_full Prediction accuracy of L- and M-cone based human pupil light models
title_fullStr Prediction accuracy of L- and M-cone based human pupil light models
title_full_unstemmed Prediction accuracy of L- and M-cone based human pupil light models
title_short Prediction accuracy of L- and M-cone based human pupil light models
title_sort prediction accuracy of l- and m-cone based human pupil light models
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7335057/
https://www.ncbi.nlm.nih.gov/pubmed/32620793
http://dx.doi.org/10.1038/s41598-020-67593-3
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